Analysis of Elementary School Students' Readiness to Learn Based on Learning Facilities at Home Using the Naive Bayes Data Mining Method
DOI:
https://doi.org/10.65310/3dbeek08Keywords:
Data Mining, Elementary School, Home Learning Facilities, learning Readiness, Naive Bayes.Abstract
Learning readiness of elementary school students is an important factor in supporting the effectiveness of the learning process. One aspect that influences learning readiness is the availability of learning facilities at home, such as a study space, textbooks, stationery, and supporting learning media. This study aims to analyze the learning readiness of elementary school students based on home learning facilities using the Naive Bayes data mining method. The research data were collected through questionnaires distributed to students and their parents and then processed through preprocessing stages to ensure data quality. The Naive Bayes algorithm was applied to classify students’ learning readiness into ready and not ready categories based on the available home learning facilities. The results indicate that home learning facilities have an influence on students’ learning readiness, and the Naive Bayes algorithm is able to provide accurate classification results. This study is expected to serve as a reference for parents and schools in improving students’ learning readiness through the provision of adequate learning facilities at home.
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Agustina, F. D., Arif, M., & Ahmad, S. (2025). Systematic Literature Review atas Kinerja Algoritma KNN, Naïve Bayes, dan Decision Tree pada Berbagai Studi Prediksi dan Klasifikasi. Jurnal Jawara Sistem Informasi, 3(1).
Amalia, F. N., & Nugraheni, N. (2024). Analisis kesiapan belajar siswa dalam mengikuti kegiatan belajar mengajar berdasarkan pembelajaran berdiferensiasi. Jurnal Riset Pendidikan Dasar (JRPD), 5(1), 21-31. https://doi.org/10.30595/jrpd.v5i1.16072
Damanik, A. R., Sumijan, S., & Nurcahyo, G. W. (2021). Prediksi tingkat kepuasan dalam pembelajaran daring menggunakan algoritma Naïve Bayes. Jurnal Sistim Informasi Dan Teknologi, 88-94. https://doi.org/10.37034/jsisfotek.v3i3.49
Dhera, M. M., Ti'a, E., Lawe, Y. U., & Sego, M. I. S. (2024). Analisis Kebutuhan Siswa serta Kesiapan Belajar Siswa Melalui Pendekatan Berdiferensiasi dalam Pembelajaran pada Siswa. Jurnal Pendidikan Guru Sekolah Dasar, 1(4), 9-9. https://doi.org/10.47134/pgsd.v1i4.827
Fanani, M. R., & Sintia, D. S. (2024). Klasifikasi Kesiapan Anak Masuk Sekolah Dasar menggunakan Algoritma Naïve Bayes dan Algoritma C4. 5. Innovative: Journal Of Social Science Research, 4(3), 10547-10555. https://doi.org/10.31004/innovative.v4i3.10425
Heryahya, A., Herawati, E. S. B., Susandi, A. D., & Zulaiha, F. (2022). Analisis kesiapan guru sekolah dasar dalam implementasi Kurikulum Merdeka. Journal of Education and Instruction (JOEAI), 5(2), 548-562.
Insani, F., Nuroso, H., & Purnamasari, I. (2023). Analisis Hasil Asemen Diagnostik Sebagai Dasar Pelaksanaan Pembelajaran Berdiferensiasi Di Sekolah Dasar. Didaktik: Jurnal Ilmiah PGSD STKIP Subang, 9(2), 4450-4458. https://doi.org/10.36989/didaktik.v9i2.1154
Juari, E. W. D. R. A., & Nugraheni, N. (2024). Analisis Kesiapan Belajar Siswa pada Pembelajaran Perdiferensiasi. Jurnal Riset Pendidikan Dasar (JRPD), 5(1), 43-51. https://doi.org/10.30595/jrpd.v5i1.16064
Kristiantari, M. R. (2014). Analisis kesiapan guru sekolah dasar dalam mengimplementasikan pembelajaran tematik integratif menyongsong kurikulum 2013. JPI (Jurnal Pendidikan Indonesia), 3(2). https://doi.org/10.23887/jpi-undiksha.v3i2.4462
Kusumaningrum, P. D., & Abduh, M. (2022). Analisis kesiapan guru sekolah dasar dalam pelaksanaan asesmen nasional. Jurnal basicedu, 6(3), 5244-5250. https://doi.org/10.31004/basicedu.v6i3.2912
Nasrullah, A. (2023). Data Mining Algoritma Naive Bayes Untuk Memprediksi Jumlah Siswa Baru. EJECTS: Journal Computer, Technology, and Informations System, 2(2), 62-67.
Pekuwali, A. A., Bano, V. O., Panja, A. D. D., & Prasetyo, F. I. (2025). Eksplorasi Variabel Berpengaruh dan Akurasi Algoritma Naive Bayes Classifier untuk Mengklasifikasikan Performa Siswa Sekolah Dasar: Exploration of Influential Variables and Accuracy of the Naive Bayes Classifier Algorithm for Classifying the Performance of Elementary School Students. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 5(3), 819-829. https://doi.org/10.57152/malcom.v5i3.1813
Rifqiyah, F., & Nugraheni, N. (2023). Analisis kesiapan belajar siswa untuk pemenuhan capaian kurikulum merdeka dengan pembelajaran berdiferensiasi. Jurnal Riset Pendidikan Dasar (JRPD), 4(2), 145-157. https://doi.org/10.30595/jrpd.v4i2.16052
Santika, N. K. N., Suantara, I. W., & Aryanthi, N. K. S. (2022). Analisis kesiapan belajar siswa kelas IV dengan kurikulum merdeka. Jurnal Pendidikan Dasar Rare Pustaka, 4(2), 1-7. https://doi.org/10.59789/rarepustaka.v4i2.124
Sayaputra, A. (2025). Implementation of Machine Learning Algorithms for Predicting Student Final GPA Using Multiclass Classification Models. Journal of Artificial Intelligence and Software Engineering, 5(2), 660-675. https://doi.org/10.30811/jaise.v5i2.7015
Setiawan, H. (2022). Klasifikasi Penerapan Pengolahan Data Mining Dalam Bidang Akademik (Doctoral dissertation, Universitas Mercu Buana Jakarta).
Sihombing, I. A., Hartama, D., Parlina, I., Gunawan, I., & Kirana, I. O. (2021). Analisis keberhasilan pembelajaran daring pada masa pandemi Covid-19 menggunakan algoritma C4. 5 dan Naive Bayes. JUKI: Jurnal Komputer dan Informatika, 3(2), 89-96. https://doi.org/10.53842/juki.v3i2.68
Susana, H. (2022). Penerapan Model Klasifikasi Metode Naive Bayes Terhadap Penggunaan Akses Internet. Jurnal Riset Sistem Informasi Dan Teknologi Informasi (JURSISTEKNI), 4(1), 1-8. https://doi.org/10.52005/jursistekni.v4i1.96
Suwayudhi, E. I., & Damanik, B. E. (2022). Teknik Klasifikasi dalam Memprediksi Penerimaan Siswa Baru Menggunakan Metode Naïve Bayes Classification Techniques in Predicting New Student Admission Using the Naïve Bayes Method. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(3), 2828-9099.
Ventura, A. B. (2021). Perbandingan Metode Data Mining K-Nearest Neighbors Dan Naïve Bayes Untuk Prediksi Kesiapan Anak Dalam Menyesuaikan Diri Di Jenjang Sekolah Dasar (Doctoral dissertation, Universitas Mercu Buana Jakarta).
Wijana, M., Nur’aeni, N. A., & Mu’minin, A. M. R. (2025). Analisis Kualitas Layanan dan Fasilitas terhadap Kepuasan Siswa menggunakan Data Mining. Jurnal Maps (Manajemen Perbankan Syariah), 8(2), 115-123. https://doi.org/10.32627/maps.v8i2.1347
Wulan Dari, S. (2025). Data Mining Untuk Klasifikasi Tingkat Selfefficacy Akademik Bagi Mahasiswa Di Kota Pekanbaru Menggunakan Metode NaÏve Bayes (Doctoral dissertation, Universitas Islam Riau).
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Copyright (c) 2026 Mesi Ana Ritonga, Sri Rahmayani parinduri, Andriansyah harahap, Muhammad Fikri Haikal (Author)
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